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Record W3153242316 · doi:10.3390/min11040421

Beneficiation Studies of the Low-Grade Skarn Phosphate from Mactung Tungsten Deposit, Yukon, Canada

2021· article· en· W3153242316 on OpenAlexafffundabout
Hao Li, Gideon Lambiv Dzemua, Qi Liu

Bibliographic record

VenueMinerals · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsGovernment of Northwest TerritoriesUniversity of Alberta
FundersUniversity of Alberta
KeywordsBeneficiationGangueSkarnScheelitePhosphate mineralsFluorapatiteApatiteCarbonateGeologySodium silicateMineralogyGeochemistryCalcitePhosphateMetallurgyQuartzChemistryTungstenMaterials scienceFluid inclusions

Abstract

fetched live from OpenAlex

A preliminary beneficiation study of low-grade skarn phosphate rocks from Mactung tungsten deposit, along the Yukon and Northwest Territories border in Canada, was carried out through standard Bond Work Index, grinding test and laboratory batch flotation tests. The skarn phosphate sample assayed 12.65% P2O5 (about 30% apatite), 31.71% CaO and 35.46% SiO2. The main gangue minerals included calcite, quartz, calc-silicates, amphibole, feldspar, and pyrrhotite. The sample had a Bond Work Index of 19.04 kWh/t, belonging to a hard ore category. The beneficiation study of the skarn phosphate sample was carried out using “direct–reverse flotation” method. The direct flotation was carried out using sodium carbonate, sodium silicate solution (water glass) and sodium oleate. Sulfuric acid and phosphoric acid were used in the reverse flotation of the carbonate gangue. One phosphorous rougher flotation, one bulk cleaner flotation and one carbonate reverse flotation at ore grind size of 86% passing 53 µm led to a phosphate concentrate assaying 28.68% P2O5, 12.06% SiO2, 0.72% MgO and 46.98% CaO, at a P2O5 recovery of 70.9%.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.248
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2021
Admission routes3
Has abstractyes

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